Computer systems are currently in wide use. Some such computer systems receive input signals and perform sequence recognition to generate a recognition result from the input signals. Examples of sequence recognition include, but are not limited to, speech recognition, handwriting recognition, character recognition, image recognition and/or computer vision. In such systems, one example machine learning task includes sequence labeling that involves an algorithmic assignment of a categorical label to each member of a sequence of observed values.
In one example speech processing system, a speech recognizer receives an audio input signal and, in general, recognizes speech in the audio signal, and may transcribe the speech into text. A speech processing system can also include a noise suppression system and/or an audio indexing system that receives audio signals and indexes various characteristics of the signal, such as a speaker identity, subject matter, emotion, etc. A speech processing system can also include speech understanding (or natural language understanding) systems, that receive an audio signal, identify the speech in the signal, and identify an interpretation of the content of that speech. A speech processing system can also include a speaker recognition system that receives an audio input stream and identifies the various speakers that are speaking in the audio stream and/or a distance of the speakers to the microphone that captured the audio input stream. Another function often performed is speaker segmentation and tracking, also known as speaker diarization.
The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.